An SMO-like algorithm for Kernel Conditional Random Fields
author:
Roland Memisevic,
University of Toronto
Categories
Top: Computer Science: Machine Learning: Kernel MethodsTop: Computer Science: Machine Learning: Graphical Models
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| Slides | |
| 0:00 | CRFs in the dual |
| 0:11 | Linear classification |
| 1:41 | Motivation |
| 4:09 | Multinomial logistic regression |
| 4:30 | Multinomial logistic regression1 |
| 4:35 | Multinomial logistic regression2 |
| 5:26 | Multinomial logistic regression3 |
| 5:30 | Multinomial logistic regression4 |
| 6:01 | Multinomial logistic regression (primal) |
| 7:13 | Multinomial logistic regression (dual) |
| 9:05 | Sequential minimal optimization |
| 11:57 | SMO |
| 14:16 | Experiments (USPS) |
| 15:31 | Conditional random fields |
| 16:29 | Conditional random fields1 |
| 16:51 | Conditional random fields2 |
| 16:55 | Conditional random fields3 |
| 16:57 | Conditional random fields4 |
| 16:59 | Conditional random fields5 |
| 17:18 | Conditional random fields6 |
| 17:20 | Conditional random fields7 |
| 17:23 | Conditional random fields8 |
| 17:29 | Conditional random fields9 |
| 17:42 | Conditional random fields10 |
| 18:14 | Conclusions |
| 20:03 | References |
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